Australia Population: Resident: Estimated: Annual: Northern Territory: Greater Darwin data was reported at 148,884.000 Person in 2017. This records an increase from the previous number of 147,102.000 Person for 2016. Australia Population: Resident: Estimated: Annual: Northern Territory: Greater Darwin data is updated yearly, averaging 131,105.500 Person from Jun 2006 (Median) to 2017, with 12 observations. The data reached an all-time high of 148,884.000 Person in 2017 and a record low of 113,461.000 Person in 2006. Australia Population: Resident: Estimated: Annual: Northern Territory: Greater Darwin data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G002: Estimated Resident Population.

As of December 2023, the proportion of the Australian population that lived in New South Wales amounted to 31.3 percent. The Northern Territory had the least number of residents in the country, with less than one percent of the population residing there.

Population: Resident: Estimated: Female: State: Northern Territory data was reported at 125,955.000 Person in Sep 2024. This records an increase from the previous number of 125,815.000 Person for Jun 2024. Population: Resident: Estimated: Female: State: Northern Territory data is updated quarterly, averaging 96,225.000 Person from Jun 1981 (Median) to Sep 2024, with 174 observations. The data reached an all-time high of 125,955.000 Person in Sep 2024 and a record low of 57,223.000 Person in Jun 1981. Population: Resident: Estimated: Female: State: Northern Territory data remains active status in CEIC and is reported by Australian Bureau of Statistics. The data is categorized under Global Database’s Australia – Table AU.G002: Estimated Resident Population.

The workforce dataset contains monthly workforce sizes from July 2005 to June 2018 in the eight Australian capital cities with estimated stratification by indoor and outdoor workers. It is included in both csv and rda format. It includes variables for:

Year Month GCCSA (Greater Capital City Statistical Area, which is used to define capital cities) Date (using the first day of the month) fulltime: Fulltime workers parttime: Parttime workers n. Overall workers outorin. Estimated indoor or outdoor status

This data are derived from the Australian Bureau of Statistics (ABS) Labour Force, Australia, Detailed, LM1 dataset: LM1 - Labour force status by age, greater capital city and rest of state (ASGS), marital status and sex, February 1978 onwards (pivot table). Occupational data from the 2006, 2011 and 2016 Census of Population and Housing (ABS Census TableBuilder Basic data) were used to stratify this dataset into indoor and outdoor classifications as per the "Indooroutdoor classification.xlsx" file. For the Census data, GCCSA for the place of work was used, not the place of usual residence.

Occupations were defined by the Australian and New Zealand Standard Classification of Occupations (ANZSCO). Each 6-digit ANZSCO occupation (the lowest level classification) was manually cross-matched with their corresponding occupation(s) from the Canadian National Occupation System (NOC). ANZSCO and NOC share a similar structure, because they are both derived from the International Standard Classification of Occupations. NOC occupations listed with an “L3 location” (include main duties with outdoor work for at least part of the working day) were classified as outdoors, including occupations with multiple locations. Occupations without a listing of "L3 location" were classified as indoors (no outdoor work). 6-digit ANZSCO occupations were then aggregated to 4-digit unit groups to match the ABS Census TableBuilder Basic data. These data were further aggregated into indoor and outdoor workers. The 4-digit ANZSCO unit groups’ indoor and outdoor classifications are listed in "Indooroutdoor classification.xlsx."

ANZSCO occupations associated with both indoor and outdoor listings were classified based on the more common listing, with indoors being selected in the event of a tie. The cross-matching of ANZSCO and NOC occupation was checked against two previous cross-matches used in published Australian studies utilising older ANZSCO and NOC versions. One of these cross-matches, the original cross-match, was validated with a strong correlation between ANZSCO and NOC for outdoor work (Smith, Peter M. Comparing Imputed Occupational Exposure Classifications With Self-reported Occupational Hazards Among Australian Workers. 2013).

To stratify the ABS Labour Force detailed data by indoors or outdoors, workers from the ABS Census 2006, 2011 and 2016 data were first classified as indoors or outdoors. To extend the indoor and outdoor classification proportions from 2005 to 2018, the population counts were (1) stratified by workplace GCCSA (standardised to the 2016 metrics), (2) logit-transformed and then interpolated using cubic splines and extrapolated linearly for each month, and (3) back-transformed to the normal population scale. For the 2006 Census, workplace location was reported by Statistical Local Area and then converted to GCCSA. This interpolation method was also used to estimate the 1-monthly worker count for Darwin relative to the rest of Northern Territory (ABS worker 1-monthly counts are reported only for Northern Territory collectively).

ABS data are owned by the Commonwealth Government under a CC BY 4.0 license. The attached datasets are derived and aggregated from ABS data.

Here we provide a catalogue of variants called after sequencing the exomes of 50 Aboriginal individuals from the Northern Territory (NT) of Australia and compare these to 72 previously published exomes from a Western Australian (WA) population of Martu origin. Sequence data for both NT and WA samples were processed using an ‘intersect-then-combine’ (ITC) approach, using GATK and SAMtools to call variants. The data is provided as 2 VCF files, one for the WA population and one for the NT population.

In the Northern Territory (NT) the Northern Territory Cancer Registry (NTCR) collects data about NT residents who are either diagnosed with cancer or die from cancer. The NTCR analyses and reports the data to provide information for health service planning and delivery, as well as for informing the general public. In this report summary statistics are presented on all new cases of cancer diagnosed among NT residents during the 15-year period 1991–2005 and on all cancer deaths during the 13- year period 1991–2003. Equivalent summary statistics for the Australian population are included for comparative purposes. Additionally, for the first time graphical representation of trends in NT cancer incidence and mortality rates are provided for each cancer site. To allow comparison of incidence rates and deaths rates within the NT population and with the wider Australian population, the rates were adjusted for the increase in total populations and for the changing age profile within the populations.

This paper describes the analysis of population data typed using the Promega PowerPlex 21 multiplex for the three major sub populations within Australia. Samples from 1427 declared Australian Aboriginal, 546 Pure Aboriginals from the Northern Territory, 990 Asian, and 1707 Caucasian individuals representing were analysed. Departures from Hardy–Weinberg equilibrium (HWE) and linkage equilibrium (LE) were assessed using exact tests. The Aboriginal populations were shown to display significant departures from equilibrium. All four subpopulation databases are of suitable size for the purpose of estimating allele frequencies.

This dataset presents the projected enrolled population at 22 August 2020 for the Northern Territory (NT) by Legislative Assembly (LA) division areas and 2016 Australian Statistical Geography Standards (ASGS) Statistical Area Level 1 (SA1). Projected elector numbers are prepared by the Australian Bureau of Statistics (ABS) according to assumptions reflecting prevailing trends agreed to by the Northern Territory Electoral Commission. This projection is indicative of future population trends and is not official ABS population statistics.

In the instance where an SA1 is divided between two or more LA divisions, the SA1 index will appear on multiple rows in the file. An individual row in the file will represent elector numbers for a whole or partial SA1 as it relates to any given LA division boundary.

For more information please visit the Northern Territory Government Open Data Portal and read the ABS Projection Assumptions Document.

Please note:

• Members of the Legislative Assembly that reside outside their electoral division are not represented in this dataset.

As of June 2023, there were approximately 8.33 million residents in the New South Wales region in Australia. In comparison, there were around 252 thousand residents in the Northern Territory region.

This dataset presents the Northern Territory (NT) elector numbers as at 15 February 2019 against 2016 Australian Statistical Geography Standard (ASGS) Statistical Area Level 1 (SA1) indexes and NT Legislative Assembly (LA) division names.

In the instance where an SA1 is divided between two or more LA divisions, the SA1 index will appear on multiple rows in the file. An individual row in the file will represent elector numbers for a whole or partial SA1 as it relates to any given LA division boundary.

For more information please visit the Northern Territory Government Open Data Portal.

Please note:

• Members of the Legislative Assembly that reside outside their electoral division are not represented in this dataset.

A total of 1737 Pinctada maxima samples were collected from eight distinct populations, six in Australia and two in Indonesia. The Australian populations were sampled from Darwin in the Northern Territory and the Lacepede Islands, 80 Mile Beach - shallow water, 80 Mile Beach - deep water, Port Hedland and Exmouth Gulf in Western Australia. The Indonesian populations were sampled from Madura Island and Sumbawa Island.Samples of both adductor muscle and mantle tissue were collected from Pinctada maxima oysters of various sizes aboard pearling industry vessels in Western Australia and the Northern Territory, between February 1998 and November 1999. Whole shell samples from the Indonesian sites, collected in November 1999, were delivered by road to Gondol Fisheries Station and held in flowing sea water tanks prior to dissection. The entire soft tissues from small spat were removed from the shell. Samples were either snap frozen in liquid nitrogen or preserved in 70% ethanol immediately following collection.Assays were developed for eight highly variable microsatellites markers and an mtDNA marker for rapid assessment of genetic variation in pearl oysters. These assays were used to screen the eight populations of P. maxima (including different juvenile age classes for the Western Australian and Northern Territory populations). It was demonstrated that the Western Australian populations belong to one stock with large effective population sizes and have little or no recruitment from Indonesia and a reasonable degree of exchange with Northern Territory. A basic technology for assessment of genetic variation in spat and for future use in improving cultured pearl oyster stocks was developed.Successful description of the population genetic structure for different age classes of Pinctada maxima in Western Australia and Northern Territory has provided a basis for improved maintenance of a productive and valuable fishery through improved stock definition and determination of levels of dispersal among populations. The development of highly variable DNA markers provides a base technology to assist the choice of sources of broodstock for hatcheries and future management of cultured populations as the Pearling Industry increasingly relies on hatchery produced spat.
The objectives of this research were:1. To develop assays for regions of highly variable DNA (microsatellites) and mtDNA markers for rapid assessment of genetic variation in pearl oysters.2. To survey up to eight populations of P. maxima throughout the Western Australian coast, including different juvenile age classes, using up to ten highly variable markers.3. To infer the level of dispersal between populations and the effective population size contributing to the next generation from the genetic data and identify the management implications of these data.4. To develop the basic technology for assessment of genetic variation in spat and for future use in improving cultured pearl oyster stocks.
Initially two sites were collected in each of 80 Mile shallow and 80 Mile deep populations. The 80 Mile shallow collections were made almost continuously between ten and eighteen mile beach and the subsets were fused into one sample. The 80 Mile deep collections were made from Cape Bossut and Compass Rose sites, the latter being more offshore than the former. These two sites showed no significant microsatellite frequency differences and were also fused.In 1998, samples were collected from Australian waters only and consisted of animals from three different year classes defined by dorso-ventral shell length, 0+ spat (1-60mm), 1+ spat (61- 120mm) and adults (>120 mm). In 1999 a second set of 0+ and 1+ spat were collected from four of the Western Australian populations (the Lacepede Islands, 80 Mile Beach, Port Hedland and Exmouth Gulf) to allow a comparison of gene frequencies for a single cohort over two successive years.

Charles Darwin University and the Northern Territory (NT) Department of Industry, Tourism and Trade (DITT) Fisheries Division used genetic data to investigate the population structure of two small tropical shark species (Milk Shark [Rhizoprionodon acutus] and Australian Blackspot Shark [Carcharhinus coatesi]), which are caught as bycatch from commercial fisheries in the NT.

The aim of this study was to gain information on the genetic stock structure to inform the future management of these two species in the NT. This project was conducted in parallel with a PhD project investigating the biology and ecology of both species for applications to fisheries management. There is motivation by the NT Government to develop these two shark species into a commercial product. This project used genetic analysis to understand the patterns of connectivity of populations of these two shark species in NT waters and adjacent regions, including Northern Western Australia and Papua New Guinea.

Background

These two shark species that are captured as bycatch in the NT Demersal Trawl fishery have the potential to be developed into a byproduct to add value to that fishery. A sustainable commercial harvest of these two species could greatly reduce the waste from fisheries, where they are currently abundant and caught in relatively large numbers. We address current knowledge gaps in biological information about populations of R. acutus and C. coatesi to inform the potential development of a byproduct fishery for these two species in the NT.

Aims

Our research aimed to:

· identify the genetic population structure for R. acutus and C. coatesi in NT waters

· develop capacity for genetic research and monitoring of shark species in the NT

· provide baseline information on genetic structure to inform potential genetic monitoring of these species, including initial estimates of effective population size.

Methods

We used single-nucleotide polymorphism genetic analyses to measure genetic structure among R. acutus and C. coatesi samples obtained from commercial trawl fishing in NT waters between May 2018 and November 2019. Our aim was to determine whether the two species each occur as a single population in NT waters or as a set of discrete populations that may warrant separate monitoring and management. We also analysed samples of these species from Western Australia and Papua New Guinea to provide broader context for the degree of genetic differentiation among the samples from different regions in the NT.

Our secondary aim was to provide a baseline for deciding whether genetic estimates of effective population size could be used to monitor trends in abundance of these species, and whether samples from across the NT could be combined for the genetic estimation of effective population size for this purpose.

Results

Genetic data from R. acutus and C. coatesi strongly suggest that each species exists as a single, highly connected population in the NT. Genetic differentiation among the sampling locations for each species was low, and genetic clustering analyses provided strong support for a single population of each species in the region. Sharks of both species captured within a single location (within 50 km of one another) were more genetically related than those further apart; however, this does not constitute evidence for multiple, spatially discrete populations of either species in NT waters. Preliminary applications of effective population size estimators were used, but further work is needed to determine if these can be used to indicate trends in abundance.

Implications for relevant stakeholders

The immediate implications of our research are for fisheries scientists and managers from NT DITT. Our results indicate that these two shark species can be monitored and managed in the NT under the assumption that each species occurs as a single population in this region. Further information relevant to shorter-term movements of individuals may refine management strategies for the two species.

Our research has potential implications for commercial fishers, particularly from the Demersal Trawl Fishery and Australia Bay Seafoods company. Currently, those implications are indirect, as the information from our research will flow through to the industry by contributing to the information required to develop a byproduct fishery for the two species, mitigating bycatch and increasing economic return.

Recommendations

Future research could develop genetic methods, such as effective population size or close-kin mark-recapture, for population monitoring. Comparing the genetic data against other data that indicate individual movement patterns on shorter timescales would help develop a holistic understanding of shark movement and population connectivity to inform sustainable harvest strategies. Methods The two datasets presented here include single nucleotide polymorphism (SNP data for the milk shark (Rhizoprionodon acutus) and the Australian blackspot shark (Carcarhinus coatesi) generated by Diversity Arrays Pty Ltd using the DArTSeq method. DArTSeq (Kilian et al 2012) involves an initial step of ‘genome reduction’ to subset a small fraction of the genome of each individual for high-throughput sequencing, followed by bioinformatics analysis to identify DNA sequences containing single nucleotide positions that vary among individuals within and among populations. The DArTSeq protocols for Carcharhinus and Rhizoprionodon are available for future projects via Diversity Arrays. Using the DArTSeq protocol, 196 individual R. acutus and 634 individual C. coatesi sampled were genotyped. The samples came from sharks that were collected in Northern Territory (Australia) waters between May 2018 and November 2019 and from three additional regions including Western Australia (Pilbara and Kimberley regions) and Papua New Guinea. Sampling locations of individuals and full unfilltered SNP genotypes are included in the dataset. Kilian, A., Wenzl, P., Huttner, E., Carling, J., Xia, L., Blois, H., Caig, V., Heller-Uszynska, K., Jaccoud, D., & Hopper, C. (2012). Diversity arrays technology: A generic genome profiling technology on open platforms. In Data production and analysis in population genomics (pp. 67–89). Springer.

Whole exome sequencing (WES) is a popular and successful technology which is widely used in both research and clinical settings. However, there is a paucity of reference data for Aboriginal Australians to underpin the translation of health-based genomic research. Here we provide a catalogue of variants called after sequencing the exomes of 50 Aboriginal individuals from the Northern Territory (NT) of Australia and compare these to 72 previously published exomes from a Western Australian (WA) population of Martu origin. Sequence data for both NT and WA samples were processed using an ‘intersect-then-combine’ (ITC) approach, using GATK and SAMtools to call variants. A total of 289,829 variants were identified in at least one individual in the NT cohort and 248,374 variants in at least one individual in the WA cohort. Of these, 166,719 variants were present in both cohorts, whilst 123,110 variants were private to the NT cohort and 81,655 were private to the WA cohort. Our data set provides a useful reference point for genomic studies on Aboriginal Australians.

Wholesalers registered to trade alcohol in the NT provide the Department of Industry, Tourism and Trade with data on the volume of alcohol supplied to licensed retailers by product type (cask wine, bottled wine, fortified wine, cider, standard spirits, pre-mixed spirits, full strength beer, mid strength beer and low strength beer). The volume of each product supplied is multiplied by its estimated fraction of alcohol content so that the amount of pure alcohol associated with each product type can be compared. The figures presented represent the wholesale supply in litres of Pure Alcohol Content (PAC). Statistics are presented for the NT as a whole; each of the major urban centres (Darwin, Palmerston, Alice Springs, Katherine, Tennant Creek and Nhulunbuy) and for the NT Balance. An estimate of the apparent per capita consumption of alcohol in the NT is determined by dividing the total alcohol supplied by an estimate of the population likely to be drinking. As the NT is a major centre for tourism, the total population likely to be drinking is derived by adding the estimates of interstate and international tourist numbers to the Australian Bureau of Statistics’ estimates of the NT population aged 15 years and over.

This dataset contains key characteristics about the data described in the Data Descriptor Reference exome data for Australian Aboriginal populations to support health-based research. Contents:

    1. human readable metadata summary table in CSV format


    2. machine readable metadata file in JSON format

This data collection contains all currently published nucleotide (DNA/RNA) and protein sequences from Australian Research Institutions in Northern Territory (NT).The nucleotide (DNA/RNA) and protein sequences have been sourced through the European Nucleotide Archive (ENA) and Universal Protein Resource (UniProt), databases that contains comprehensive sets of nucleotide (DNA/RNA) and protein sequences from all organisms that have been published by the International Research Community.

Incidence of NS in the NT based on different criteria.

A study of the population genetics of the prawn Penaeus monodon in northern and eastern Australian waters. Mitochondrial D-loop DNA (and Restriction Fragment Length Polymorphism - RFLP) were used to estimate connectivity and dispersal between populations which range through locations in Western Australia, Northern Territory, Queensland and New South Wales. Statistical analyses and clustering procedures were carried out.Collection of samples were from 6 locations throughout the species range in Australia: Townsville, Cairns, Weipa, Melville Island, Joseph Bonaparte Gulf, De Grey River.Some comparison was made with Indonesian and South African samples, see separate metadata record.Microsatellite markers were used in a further study of genetic variation among the Australian populations above. To estimate connectivity and dispersal between Penaeus monodon populations in northern and eastern Australia.To compare results with genetic analyses using allozymes. Separate metadata records apply for data relating to the genetic analyses using allozymes of Penaeus monodon from Australian waters and South Africa.

A study of the population genetics of the prawn Penaeus monodon in northern and eastern Australian waters. Variations in gene frequencies of allozymes and common proteins (GPI,LGG,LT-1,MDH-1,MDH-2,MPI,PGDH,PGM) were used to estimate connectivity and dispersal between populations which range through locations in Western Australia, Northern Territory, Queensland and New South Wales. Statistical analyses and clustering procedures were carried out.Collection of samples were from 7 locations throughout the species range in Australia: Clarence River, Townsville, Cairns, Weipa, Melville Island, Joseph Bonaparte Gulf, De Grey River.A later study was conducted on South Afican samples, see separate metadata record.
To estimate connectivity and dispersal between Penaeus monodon populations in northern and eastern Australia.
First systematic survey of genetic variation of P. monodon populations over a wide geographic range. Highly significant differences between western and the northern and eastern populations were demonstrated.

This dataset presents the footprint of the percentage of adults who saw three or more health professionals for the same condition in the preceding 12 months. The data spans the years of 2014-2017 and is aggregated to 2015 Department of Health Primary Health Network (PHN) areas, based on the 2011 Australian Statistical Geography Standard (ASGS).

The data is sourced from the Australian Bureau of Statistics (ABS) 2016-17 Patient Experience Survey, collected between 1 July 2016 and 30 June 2017. It also includes data from previous Patient Experience Surveys conducted in 2013-14, 2014-15 and 2015-16. The Patient Experience Survey is conducted annually by the ABS and collects information from a representative sample of the Australian population. The Patient Experience Survey is one of several components of the Multipurpose Household Survey, as a supplement to the monthly Labour Force Survey. The Patient Experience Survey collects data on persons aged 15 years and over, who are referred to as adults for this data collection.

For further information about this dataset, visit the data source:Australian Institute of Health and Welfare - Patient experiences in Australia Data Tables.

Please note:

• AURIN has spatially enabled the original data using the Department of Health - PHN Areas.

• Percentages are calculated based on counts that have been randomly adjusted by the ABS to avoid the release of confidential data.

• As an indication of the accuracy of estimates, 95% confidence intervals were produced. These were calculated by the ABS using standard error estimates of the proportion.

• Some of the patient experience measures for 2016-17 have age-standardised rates presented. Age-standardised rates are hypothetical rates that would have been observed if the populations studied had the same age distribution as the standard population.

• Crude rates are provided for all years. They should be used for understanding the patterns of actual service use or level of experience in a particular PHN.

• The Patient Experience Survey excludes persons aged less than 15 years, persons living in non-private dwellings and the Indigenous Community Strata (encompassing discrete Aboriginal and Torres Strait Islander communities).

• Data for Northern Territory should be interpreted with caution as the Patient Experience Survey excluded the Indigenous Community Strata, which comprises around 25% of the estimated resident population of the Northern Territory living in private dwellings.

• NP - Not available for publication. The estimate is considered to be unreliable. Values assigned to NP in the original data have been set to null.